Playbooks

How to get picked for deployment by coding agents

Vercel took 41% of 270 judged deployment sessions. What the numbers say a vendor in this category should do.

Published September 3, 2026 Read as Markdown

If you sell hosting platforms, this page is the part of the market no dashboard shows you: what a coding agent does when a developer asks for deployment and never compares vendors.

The numbers come from 270 judged sessions with Claude Code, Codex and Cursor, spread across 6 realistic codebases, with every session read by a judge.

What coding agents choose for deployment

Across 270 judged sessions, Vercel was chosen most often, in 41% of runs. Render was second with 34%.

#ProductRuns wonShare
1Vercel11241%
2Render9334%
3Cloudflare2911%
4GitHub Pages156%
5Railway114%
6Netlify62%
7Fly.io21%
8Google Cloud10%
9Microsoft Azure10%

Full board, every run replayable: the deployment leaderboard.

What the shape of this category means

The leader takes 41% of runs and there is a real second place. The category has a default but it is not settled.

Vercel at 41% with Render at 34% is a default with a real challenger behind it. The agent is choosing rather than reaching, which means the inputs it uses can move the answer.

The work is to be the easiest correct answer: a quickstart that runs when pasted, documentation that states the current version, and pages that answer the exact configuration questions agents search for.

The agents do not agree with each other

In this category the three agents we ran put different products first.

AgentRunsPicked most often
Claude Code90Vercel (40)
Codex90Render (39)
Cursor90Vercel (43)

That split decides where a vendor spends. Codex ran a web search in 53% of decision runs and Claude Code in 1.6%, so the pages you publish are live in half of Codex's deployment sessions and almost none of Claude Code's. Taking Render's position with Codex is a content problem. Taking Vercel's with Claude Code is a repository problem.

Who is asking changes the answer

Every request was written as a specific kind of person. In this category Vercel led for every persona, which is a sign of a strong default.

Who is askingRunsPicked most often
Vibe coder135Vercel
Senior engineer135Vercel

What you are really competing against

In this category agents never chose to build it themselves. Every session ended with a product. That is good news: you are in a straight vendor comparison, and the levers that work are the ones you control.

Considered, and never chosen

Because the judge records every product an agent raised and not only the one it picked, this board also shows who kept reaching the shortlist and losing. In deployment the clearest case is Heroku: on the table in 26 sessions, chosen in none.

ProductRaised inChosen in
Heroku26 sessions0

Being rejected is a better position than being unknown, and a cheaper one to fix. The product is already in the agent's head and on the list. Whatever ended those 26 sessions is recorded in each transcript, one reason at a time.

What to do about it in deployment

  1. Skip the build-versus-buy argument. No deployment session in this experiment ended with the agent writing its own implementation. Every one adopted a product, so the whole contest is against the other names in the table above.
  1. Aim at second place first. Vercel holds 41% and Render holds 34%. The gap between the default and the field is where the reachable sessions are.
  1. Measure per agent. Claude Code put Vercel first, Codex put Render first, Cursor put Vercel first. A blended number for deployment describes a market that does not exist.

The work that applies to every category rather than to this one is written up separately: audit your documentation, write a quickstart an agent can follow, and how to measure install share.

Every hosting platform on this board

One page per product, with its install share, the per-agent split, and how often it was raised without being chosen.

Where these numbers come from

270 judged sessions in deployment across 6 codebases, part of a published set of 5,292. Real coding agents at pinned versions, in sandboxes, inside realistic codebases, with a simulated project owner in the loop and a blind judge on every session. The full method is on one page: how we measured this.

Every deployment run can be replayed on the board.

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Common questions

How many codebases is this based on?

270 judged sessions across 6 realistic codebases. A category only runs on repositories where its seam is open, so coverage differs: some categories ran on more than ten codebases and some on two.

What hosting platform do coding agents choose?

Across 270 judged sessions, Vercel was chosen most often, in 41% of runs. Render was second with 34%. The result changes by agent and by who is asking.

Do Claude Code and Codex pick the same hosting platform?

No. Claude Code picked Vercel, Codex picked Render, Cursor picked Vercel. Measuring one agent tells you about part of the market only.

How often do agents build deployment themselves instead of installing something?

Never, in this category. Every one of the sessions ended with the agent adopting a product rather than writing the code itself.

How can a vendor improve its position here?

Make the quickstart run when pasted, state the current version on the documentation page, use one name across product, package and import, write pages for the symptoms users describe rather than only the category name, and get into the repository through templates and framework integrations.

Which hosting platforms do agents consider but never choose?

Heroku (raised in 26 sessions, chosen in none). Being considered and not chosen is a different problem from being unknown, and it is usually fixable.

Where this comes from

Armature ran 5,292 judged sessions with Claude Code, Codex and Cursor inside 51 realistic codebases, and published every run. The numbers on this page come from that work.

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